Journal: International Dental Journal

Article Title: Obesity as a Determinant of Periodontal Therapy Outcomes: Insights on Oxidative and Endoplasmic Reticulum Stress Pathways

doi: 10.1016/j.identj.2026.109472

Figure Lengend Snippet: Oxidative stress markers in the study population, stratified by obesity presence, before and after non-surgical periodontal treatment. Total ROS (A and G), cytosolic superoxide (B and H) and mitochondrial superoxide (C and I) in leukocytes, and protein levels of SOD1 (D and J) in PBMCs normalized to the loading control actin with corresponding WB images (E), and serum total antioxidant capacity (F and K). Data are presented as box and whisker plots and were compared using two-factor analysis of variance (ANOVA) followed by post hoc tests. ** P < .01 when comparing baseline vs 12 wk. # P < .05 when comparing groups with vs without obesity. DCFH, diclorodihidrofluoresceína; dHE, dihydroethidium; MitoSOX, Mitochondrial Superoxide Indicator; ns, not significant; PBMCs, peripheral blood mononuclear cells; ROS, reactive oxygen species; SOD1, superoxide dismutase 1.

Article Snippet: Peripheral blood mononuclear cells (PBMCs) comprising monocytes and lymphocytes were isolated from EDTA-collected blood using the MACSprep PBMC Isolation Kit (Miltenyi Biotec, Teterow, Germany), and 5 × 106 cells were used for protein extraction, quantification, and Western blot (WB) analysis.

Techniques: Control, Whisker Assay

Journal: International Dental Journal

Article Title: Obesity as a Determinant of Periodontal Therapy Outcomes: Insights on Oxidative and Endoplasmic Reticulum Stress Pathways

doi: 10.1016/j.identj.2026.109472

Figure Lengend Snippet: Evaluation of UPR markers in PBMCs from study population, stratified by presence of obesity, before and after non-surgical periodontal treatment. Relative protein expression of GRP78 (A and G), ATF6 (B and H), CHOP (C and I), IRE1α (D and J), p-eIF2α (E and K), relative mRNA expression of sXBP1 (F and L) in PBMCs normalized to the loading control actin and representative WB images (M). Data are presented as box and whisker plots and were compared using two-factor analysis of variance (ANOVA) followed by post hoc tests. * P < .05; ** P < .01 when comparing baseline vs 12 wk. ATF6, activating transcription factor 6; BMI, body mass index; CHOP, C/EBP homologous protein; GRP78, Glucose-regulated protein 78; IRE1α, Inositol requiring enzyme 1α; PBMCs, peripheral blood mononuclear cells; p-eIF2α, Phosphorylated eukaryotic translation initiation factor 2 subunit; sXBP1 , spliced Xbox binding protein 1 gene.

Article Snippet: Peripheral blood mononuclear cells (PBMCs) comprising monocytes and lymphocytes were isolated from EDTA-collected blood using the MACSprep PBMC Isolation Kit (Miltenyi Biotec, Teterow, Germany), and 5 × 106 cells were used for protein extraction, quantification, and Western blot (WB) analysis.

Techniques: Expressing, Control, Whisker Assay, Binding Assay

Journal: iScience

Article Title: Profiling biological effects of microbiome metabolites via machine learning

doi: 10.1016/j.isci.2026.115282

Figure Lengend Snippet: Machine learning model validation using external datasets and prospective in vitro experiments (A) Odds ratios of predicted positives in external validation sets relative to the microbiome background. The HIA model (GUTSY, n = 50) and BBB model (NIAGADS, n = 151) showed significant enrichment (ORs = 6.0 and 2.3, respectively; Fisher’s exact test, p = 2 × 10 −4 and p = 5 × 10 −4 , respectively). (B–D) Prospective in vitro validation of drug-induced liver injury prediction in HepG2 cells. (C) Predicted liver-toxic metabolites exhibited dose-dependent, significant cytotoxic effects. (D) Predicted liver-safe metabolites showed no significant cytotoxic effect ( p > 0.05) at any of the tested concentrations up to 1 mM (unpaired t test; N = 3, n = 3). (E) Confusion matrix for the prospective in vitro validation. (F) Evaluation of performance of machine learning models predicting IL-8 secretion stimulation. The RF model outperformed each of the other models (∗ p ≤ 0.05, ∗∗ p ≤ 0.01, ∗∗∗ p ≤ 0.001, ∗∗∗∗ p ≤ 0.0001). (G) Chemical structures of top predicted candidates, spermine and spermidine. (H) Results from the IL-8 secretion assay using human PBMCs, evaluating the effect of seven microbiome metabolites at 100 μM ( N = 1, n = 3). Metabolites stimulating IL-8 are shown in pink, and metabolites with no IL-8 secretion are shown in blue (∗ p ≤ 0.05, ∗∗ p ≤ 0.01, ∗∗∗ p ≤ 0.001, ∗∗∗∗ p ≤ 0.0001). (I) IL-8 stimulation by spermine and spermidine at different concentrations ( N = 2, n ≥ 2). Data are represented as the mean ± standard deviation.

Article Snippet: Primary human peripheral blood mononuclear cell (PBMC) , ATCC , PCS-800-011, Lot 8032322.

Techniques: Biomarker Discovery, In Vitro, Standard Deviation

Journal: Nature Aging

Article Title: p21 + TREM2 + senescent macrophages fuel inflammaging and metabolic dysfunction-associated steatotic liver disease

doi: 10.1038/s43587-026-01101-6

Figure Lengend Snippet: a , Illustration of the in vitro model system using exogenous DNA damage with irradiation and Doxo on PBMC-derived macrophages from male and female human donors. b , Mean ± s.e. gene expression (RT–qPCR) normalized to control. n = 9 donors (mixed male and female) for control and Sen(IR) conditions. n = 8 for Sen(Doxo) conditions. P value from Tukey’s test post repeated measures ANOVA analysis. c , SDS–PAGE gels and immunostaining (western blot) for p21 and p16 in response to 10 days post DNA damage. ImageJ quantification for band intensity is shown to the right and represents relative intensity over the loading control. d , SA-β-gal images of human senescent macrophages. e , Click-iT EdU labeling of cells to assess proliferation dynamics. Axes represent the percentage of cells positive for the stain relative to the parental gate, as detected by flow cytometry. The bar plot represents the mean ± s.e. of n = 3 independent donors. P value derived from unpaired one-sided t -test. f , PCA on bulk RNA-seq samples from 10 days post DNA damage for three blood donors. g , Heatmap projection of all statistically significant DEGs compared to control conditions. h , KEGG pathway enrichment analysis for the top ten pathways downregulated in human senescent macrophages. i , KEGG pathway enrichment analysis for the top ten pathways upregulated in human senescent macrophages. j , Model illustration of running MSen score on publicly accessible single-cell dataset of human liver biopsy samples from five people with liver cirrhosis and five with a healthy liver. k , UMAP projection of all annotated CD45 + cell types and colored by human MSen Seurat score. l , UMAP projection of CD68 + cells (macrophages) in healthy and cirrhotic tissue samples. Color denotes human MSen Seurat score. m , Distribution of MSen Seurat score across resident macrophage (Kupffer cells) and non-resident monocyte and macrophage populations in healthy and cirrhotic conditions. P value represents the results of a two-sided t -test. n , Distribution of human MSen score across all CD45 + cell types in the dataset. ALD, alcohol-related liver disease; F, female; KC, Kupffer cell; IgA, immunoglobulin A; IL-C, innate lymphoid cell; M, male; MoMac, monocyte-derived macrophage; Mø, macrophage; PBC, primary biliary cholangitis; pDC, plasmacytoid dendritic cell. Panels a and j created in BioRender; Salladay-Perez, I. https://biorender.com/6umuckd (2026).

Article Snippet: Mouse BMDM-derived and human PBMC-derived macrophage cultures were lysed with RNA STAT 60 (Amsbio) and ~50 ng per μl of RNA was submitted to the UCLA’s Technology Center for Genomics and Bioinformatics (TCGB) core for library preparation and 2 × 100 paired-end sequencing.

Techniques: In Vitro, Irradiation, Derivative Assay, Gene Expression, Quantitative RT-PCR, Control, SDS Page, Immunostaining, Western Blot, Labeling, Staining, Flow Cytometry, RNA Sequencing, Single Cell